Operasionalisasi Konsep

Operasionalisasi Konsep (Endah Triastuti)

Theories

Empirical Generalizations

DEDUCTION

INDUCTION

Generalized Wheel of Social Science

Hypotheses Observations

Constructing a Deductive Theory 1. 2. 3. 4. 5.

Specify the topic. Specify the range of phenomena your theory addresses. Identify and specify your major concerns and variables. Find out what is known about the relationships among the variables. Reason from those propositions to the topic you are interested in.

Research design – operationalization of variables • •

– Chapter 6 in Babbie & Mouton (2001) The construction of actual, concrete measurement techniques; the creation of “operations” that will result in the desired measurements. The development or choice of specific research procedures (operations) that will result in representing the concepts of interest.

Operationalization • • • •

turning the research subject (term, issue, process, phenomenon) into variables that can be investigated by empirical data makes a term concrete from theory to empirical analysis good operationalization corresponds to the meaning to the term (within the particular study); measures what one wanted to measure; is measurable

Operationalization • An operational definition is a procedure for classifying, ordering, or quantifying something – Classifying - crowded or not crowded – Ordering - uncrowded, mildly crowded, severely crowded – Quantifying - measure crowdedness in terms of the number of residents per square kilometre • Focus on questionnaires – other operationalization techniques in section on types of research design Choices to be made about operationalization • The range of variation – how large should your categories be? – Depends on the purpose of your study – pragmatic considerations (e.g. income) • Variation between the extremes – how fine are the disctinctions you want to make in your study? • e.g. age – Again, depends on the purpose of your study – (Why research is such a challenging task – very few recipes) • Single or multiple indicators of variables – Some straightforward, such as gender – But others benefit from multiple indicators Conceptualization • The process through which we specify what we mean when use particular terms in research is called conceptualization. • The result is called a concept • Concepts have specific and agree-upon meanings. Conceptualization – = the process of identifying and clarifying concepts; through which we specify what we mean by using certain terms – Indicators indicate the presence or absence of the concept we are studying. These often are multi-dimensional; they have more than one specifiable aspect of facet. E.g. happiness. – We want to speak of abstract things – “intelligence”; “ability to cope with stress”; “life satisfaction”; “happiness”. – We cannot research these things until we know exactly what they are. – Everyday language often vague and unspecified meanings. Conceptualization is to specify exactly what we mean and don’t mean by the terms we use in our research. – No “true” (final) definitions of “the stuff of life” Variable, Dimensions and Indicators of Concepts • Dimension : a specific aspect of a concept

• • •

Variable: variance of a concept An Indicator : the presence or absence of the concept During conceptualization and operationalization, we often specify different indicators to represent different dimensions of a concept.

Operationalization: developing specific research procedures to be used in empirical observations representing those concepts Consider: Range of variation Degree of precision Operational definitions • Specifying exactly what we are going to observe, and how we will do it. Turn your variable into a directly measurable thing • It is a description of the “operations” that we will undertake to measure a concept Measurement Process: Conceptualization & Operationalization • Conceptualization conceptual definition • Operationalization operational definition Four Levels of Measurement • Nominal Measures : differences among categories – Ex: gender, religious affiliation, college major • Ordinal Measures : categories can be ordered or ranked – Ex: social class, prejudice • Interval Measures : can specify the distance between categories – Ex: IQ scores • Ratio Measures : attributes are based on a true zero point – Ex: age, # of times married, length of residence in a given place VARIABLES • Univariat: satu variabel Kebanyakan mahasiswa UI paling tidak mengunjungi bioskop sekali seminggu Variabel: Frekuensi mengunjungi bioskop • Bivariat: dua variabel Mahasiswa perempuan mengunjungi bioskop lebih sering dibandingkan laki-laki Variabel: 1) jenis kelamin, 2) frekuensi ke bioskop • Multivariat: banyak variabel Diantara mahasiswa yang mengalami depresi, laki-laki lebih sering mengunjungi bioskop dibandingkan perempuan. Tetapi, diantara mahasiswa yang tidak mengalami depresi, perempuan lebih sering mengunjungi bioskop. Variabel: 1)sex, 2) frekuensi ke bioskop, 3) kondisi depresi atau tidak